Overcoming Difficult to Inspect Multi-Diameter, Low Pressure Gas Transmission Pipeline Challenges

2018 ◽  
Author(s):  
Frank Dauby ◽  
Stefan Vages
Keyword(s):  
Low Pressure ◽  
Tool Design ◽  
Operating Conditions ◽  
Compressed Air ◽  
Quality Data ◽  
Data Set ◽  
Transmission Pipeline ◽  
Pump Testing ◽  
Lower Tool

Pacific Gas and Electric Company owns and operates an extensive network of over 10,700 km (6,700 miles) of gas transmission pipelines, much of which is under 16″ diameter and operates at less than 27.5 bar (400 psig), making them difficult to inspect with free swimming in-line inspection (ILI) tools. Additionally, many piggable pipeline sections are multi-diameter and have numerous 1.5D fittings, some of these in back to back configuration, requiring tools that are not currently available. Following several failed attempts to inspect PG&E’s 12″ × 16″ pipelines in 2015 using existing ILI tools, and after working to modify a 12″ × 18″ tool for lower pressure service in 2016, PG&E and ROSEN decided to collaboratively develop new, specially designed, 12″ × 16″ geometry and axial MFL tools. The goal of this project was to develop tools that could meet both the PG&E pipeline passage requirements and allow for an acceptable speed profile. The need to inspect a total of 16 pipeline sections in the long-term ILI Upgrade Plan, in this size range, justified the investment in these new tools. The service provider embarked on a new ILI tool design process including design, manufacturing, fabrication and testing at their facilities in Germany. Through this process, a number of unique ILI tool design features to lower tool drag and improve ease of collapsibility were implemented, resulting in a tool that far exceeds existing industry capabilities. To confirm the tools’ capabilities before their first use in a live gas transmission pipeline, pump testing in water, as well as in compressed air, was performed. In late 2017, using these tools, PG&E inspected two previously unpiggable 12″ × 16″ low-pressure pipelines successfully. In this paper, the process of developing these tools will be discussed. The test program will be reviewed comparing findings under controlled conditions in water and compressed air with pig run behavior in the live pipelines. The analysis also provides an assessment of the operating conditions that are deemed necessary for the inspection tool to gather a good quality data set.

scholarly journals Snow and ice applications of AVHRR in polar regions: report of a workshop held in Boulder, Colorado, 20 May 1992

1993 ◽  
Vol 17 ◽  
pp. 1-16 ◽  
Author(s):  
K. Steffen ◽  
R. Bindschadler ◽  
G. Casassa ◽  
J. Comiso ◽  
D. Eppler ◽  
...  
Keyword(s):  
Sea Ice ◽  
Satellite Data ◽  
Quality Data ◽  
Polar Regions ◽  
Data Set ◽  
Ice Surface ◽  
The Status ◽  
Ice Surface Temperature ◽  
Snow And Ice

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17–22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.

scholarly journals Snow and ice applications of AVHRR in polar regions: report of a workshop held in Boulder, Colorado, 20 May 1992

1993 ◽  
Vol 17 ◽  
pp. 1-16 ◽  
Author(s):  
K. Steffen ◽  
R. Bindschadler ◽  
G. Casassa ◽  
J. Comiso ◽  
D. Eppler ◽  
...  
Keyword(s):  
Sea Ice ◽  
Satellite Data ◽  
Quality Data ◽  
Polar Regions ◽  
Data Set ◽  
Ice Surface ◽  
The Status ◽  
Ice Surface Temperature ◽  
Snow And Ice

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17–22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.

scholarly journals Natural Circulation Characteristics at Low-Pressure Conditions through PANDA Experiments and ATHLET Simulations

2008 ◽  
Vol 2008 ◽  
pp. 1-14 ◽  
Author(s):  
Domenico Paladino ◽  
Max Huggenberger ◽  
Frank Schäfer
Keyword(s):  
Numerical Simulations ◽  
Large Scale ◽  
Natural Circulation ◽  
Low Pressure ◽  
Operating Conditions ◽  
Quality Data ◽  
Experimental Investigations ◽  
Stability Performance ◽  
Wide Range ◽  
Circulation Characteristics

Natural circulation characteristics at low pressure/low power have been studied by performing experimental investigations and numerical simulations. The PANDA large-scale facility was used to provide valuable, high quality data on natural circulation characteristics as a function of several parameters and for a wide range of operating conditions. The new experimental data allow for testing and improving the capabilities of the thermal-hydraulic computer codes to be used for treating natural circulation loops in a range with increased attention. This paper presents a synthesis of a part of the results obtained within the EU-Project NACUSP “natural circulation and stability performance of boiling water reactors.” It does so by using the experimental results produced in PANDA and by showing some examples of numerical simulations performed with the thermal-hydraulic code ATHLET.

scholarly journals The VISCACHA survey – deep and resolved photometry of star clusters in the Magellanic Clouds

2019 ◽  
Vol 14 (S351) ◽  
pp. 89-92
Author(s):  
Bruno Dias ◽  
Francisco Maia ◽  
Leandro Kerber ◽  
João F. C. dos Santos ◽  
Eduardo Bica ◽  
...  
Keyword(s):  
Structural Parameters ◽  
Star Clusters ◽  
Magellanic Clouds ◽  
Quality Data ◽  
Data Set ◽  
Density Profiles ◽  
Spatially Resolved ◽  
Photometric Observations ◽  
Low Mass

AbstractThe VISCACHA (VIsible Soar photometry of star Clusters in tApii and Coxi HuguA†) Survey is an ongoing project based on deep and spatially resolved photometric observations of Magellanic Cloud star clusters, collected using the SOuthern Astrophysical Research (SOAR) telescope together with the SOAR Adaptive Module Imager. So far we have used >300h of telescope time to observe ∼150 star clusters, mostly with low mass (M < 104M⊙) on the outskirts of the LMC and SMC. With this high-quality data set, we homogeneously determine physical properties using deep colour-magnitude diagrams (ages, metallicities, reddening, distances, mass, luminosity and mass functions) and structural parameters (radial density profiles, sizes) for these clusters which are used as a proxy to investigate the interplay between the Magellanic Clouds and their evolution. We present the VISCACHA survey and its initial results, based on our first two papers. The project’s long term goals and expected legacy to the community are also addressed.

Thirty years of hourly dissolved oxygen in a large shallow river illustrates discrepancy between a primary producer tipping point and river metabolism

2020 ◽  
Author(s):  
Jacob Diamond ◽  
Florentina Moatar ◽  
Matthew Cohen ◽  
Alain Poirel ◽  
Cécile Martinet ◽  
...  
Keyword(s):  
Dissolved Oxygen ◽  
Primary Production ◽  
Chlorophyll A ◽  
High Frequency ◽  
Tipping Point ◽  
Quality Data ◽  
Water Quality Data ◽  
Data Set ◽  
Primary Producer

&lt;p&gt;Large-scale efforts to reduce cultural eutrophication of freshwater systems have had varied success because internal feedbacks can stabilize the high nutrient, high productivity, and turbid conditions associated with eutrophic systems. We examined these feedbacks using a unique 40-year water quality data set from the middle Loire River, France, where phosphorus and phytoplankton concentrations have decreased by an order of magnitude from 1980&amp;#8211;2018. We focused on ecosystem metabolism as an integrative measure to elucidate cause-effect relationships of both bottom-up (e.g., nutrient concentrations) and top-down (e.g., consumer populations) effects on river trophic state.&lt;/p&gt;&lt;p&gt;The dataset combined both long-term (30 years), high-frequency (hourly) measurements of dissolved oxygen (DO) and long-term (40 years), low-frequency (monthly) measures of nutrients, plus several supporting biological surveys of primary producer and consumer densities. Using hourly measurements of DO, we estimated gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP = GPP &amp;#8211; ER), and from the resulting long time series of metabolic fluxes, we tested the hypothesis that GPP and ER responded to changes in water column concentrations of algal pigments (chlorophyll a) and phosphorus. We further tested the hypothesis that change points in the patterns of ecological behavior were contemporaneous with notable changes in river management.&lt;/p&gt;&lt;p&gt;Despite well-established links between phosphorus, chlorophyll-a and primary production, GPP was resilient to the drastic reductions in both P concentrations and phytoplankton. Indeed, GPP has only recently decreased (~25%), despite chlorophyll-a concentrations reaching a new minima 10 years earlier in response to colonization of the invasive Corbicula sp. clam in the year 2000. Declines in ER are only half (~12%) the decline in GPP, shifting the river from an autotrophic state (i.e., positive NEP) to a heterotrophic state (i.e., negative NEP). Moreover, Granger causality analysis suggested that daily primary production and respiration have decoupled over this period. With earlier phytoplankton dominance, daily ER was strongly linked to recent autochthonous GPP, but more recently daily GPP has far less influence on subsequent ER. We interpret this partially as a reduction in carbon and nutrient turnover rates resulting from the community shift from algae to macrophytes, and attendant changes in nutrient sources (now primarily from sediment) and carbon stocks (now principally in the sediment). This study illustrates the benefit of long-term high-frequency data collection for understanding pattern and process in aquatic ecosystems, and illustrates a compelling example of process resilience contrasted with an ecosystem tipping point in the context of global change.&lt;/p&gt;

scholarly journals Detecting dominant changes in irregularly sampled multivariate water quality data sets

2018 ◽  
Vol 22 (8) ◽  
pp. 4401-4424
Author(s):  
Christian Lehr ◽  
Ralf Dannowski ◽  
Thomas Kalettka ◽  
Christoph Merz ◽  
Boris Schröder ◽  
...  
Keyword(s):  
Water Quality ◽  
Stream Water ◽  
Shallow Groundwater ◽  
Irregular Sampling ◽  
Quality Data ◽  
Data Sets ◽  
Water Quality Data ◽  
Data Set ◽  
Sampling In Space

Abstract. Time series of groundwater and stream water quality often exhibit substantial temporal and spatial variability, whereas typical existing monitoring data sets, e.g. from environmental agencies, are usually characterized by relatively low sampling frequency and irregular sampling in space and/or time. This complicates the differentiation between anthropogenic influence and natural variability as well as the detection of changes in water quality which indicate changes in single drivers. We suggest the new term “dominant changes” for changes in multivariate water quality data which concern (1) multiple variables, (2) multiple sites and (3) long-term patterns and present an exploratory framework for the detection of such dominant changes in data sets with irregular sampling in space and time. Firstly, a non-linear dimension-reduction technique was used to summarize the dominant spatiotemporal dynamics in the multivariate water quality data set in a few components. Those were used to derive hypotheses on the dominant drivers influencing water quality. Secondly, different sampling sites were compared with respect to median component values. Thirdly, time series of the components at single sites were analysed for long-term patterns. We tested the approach with a joint stream water and groundwater data set quality consisting of 1572 samples, each comprising sixteen variables, sampled with a spatially and temporally irregular sampling scheme at 29 sites in northeast Germany from 1998 to 2009. The first four components were interpreted as (1) an agriculturally induced enhancement of the natural background level of solute concentration, (2) a redox sequence from reducing conditions in deep groundwater to post-oxic conditions in shallow groundwater and oxic conditions in stream water, (3) a mixing ratio of deep and shallow groundwater to the streamflow and (4) sporadic events of slurry application in the agricultural practice. Dominant changes were observed for the first two components. The changing intensity of the first component was interpreted as response to the temporal variability of the thickness of the unsaturated zone. A steady increase in the second component at most stream water sites pointed towards progressing depletion of the denitrification capacity of the deep aquifer.

scholarly journals An Ensemble Prognostic Method of Francis Turbine Units Using Low-Quality Data under Variable Operating Conditions

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 525
Author(s):  
Ran Duan ◽  
Jie Liu ◽  
Jianzhong Zhou ◽  
Pei Wang ◽  
Wei Liu
Keyword(s):  
Prediction Model ◽  
Prediction Interval ◽  
Gaussian Mixture ◽  
Operating Conditions ◽  
Monitoring Data ◽  
Francis Turbine ◽  
Quality Data ◽  
Percentage Error ◽  
Data Set ◽  
Operation Conditions

The prognostic is the key to the state-based maintenance of Francis turbine units (FTUs), which consists of performance state evaluation and degradation trend prediction. In practical engineering environments, there are three significant difficulties: low data quality, complex variable operation conditions, and prediction model parameter optimization. In order to effectively solve the above three problems, an ensemble prognostic method of FTUs using low-quality data under variable operation conditions is proposed in this study. Firstly, to consider the operation condition parameters, the running data set of the FTU is constructed by the water head, active power, and vibration amplitude of the top cover. Then, to improve the robustness of the proposed model against anomaly data, the density-based spatial clustering of applications with noise (DBSCAN) is introduced to clean outliers and singularities in the raw running data set. Next, considering the randomness of the monitoring data, the healthy state model based on the Gaussian mixture model is constructed, and the negative log-likelihood probability is calculated as the performance degradation indicator (PDI). Furthermore, to predict the trend of PDIs with confidence interval and automatically optimize the prediction model on both accuracy and certainty, the multiobjective prediction model is proposed based on the non-dominated sorting genetic algorithm and Gaussian process regression. Finally, monitoring data from an actual large FTU was used for effectiveness verification. The stability and smoothness of the PDI curve are improved by 3.2 times and 1.9 times, respectively, by DBSCAN compared with 3-sigma. The root-mean-squared error, the prediction interval normalized average, the prediction interval coverage probability, the mean absolute percentage error, and the R2 score of the proposed method achieved 0.223, 0.289, 1.000, 0.641%, and 0.974, respectively. The comparison experiments demonstrate that the proposed method is more robust to low-quality data and has better accuracy, certainty, and reliability for the prognostic of the FTU under complex operating conditions.

Configurations to Superior Environmental Innovation Strategy: A Both–And Approach

2021 ◽  
pp. 108602662110316
Author(s):  
Tiziana Russo-Spena ◽  
Nadia Di Paola ◽  
Aidan O’Driscoll
Keyword(s):  
Climate Change ◽  
Value Chain ◽  
Critical Role ◽  
Well Being ◽  
Point Of View ◽  
Future Generations ◽  
Innovation Strategy ◽  
Environmental Innovation ◽  
Data Set

An effective climate change action involves the critical role that companies must play in assuring the long-term human and social well-being of future generations. In our study, we offer a more holistic, inclusive, both–and approach to the challenge of environmental innovation (EI) that uses a novel methodology to identify relevant configurations for firms engaging in a superior EI strategy. A conceptual framework is proposed that identifies six sets of driving characteristics of EI and two sets of beneficial outcomes, all inherently tensional. Our analysis utilizes a complementary rather than an oppositional point of view. A data set of 65 companies in the ICT value chain is analyzed via fuzzy-set comparative analysis (fsQCA) and a post-QCA procedure. The results reveal that achieving a superior EI strategy is possible in several scenarios. Specifically, after close examination, two main configuration groups emerge, referred to as technological environmental innovators and organizational environmental innovators.

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